--- title: "Tableone_Dryad" output: html_document --- ```{r} library(tableone) ``` ```{r} setwd("Z:/Kleer/Project Paper/Masterfiles/4. Testfiles/") #setwd("/Volumes/KLIM$/Kleer/Project Paper/Masterfiles/4. Testfiles") #setwd("/Volumes/KLIM$/Kleer/Project Paper/Submission/DRYAD") ``` ```{r} #read in data data <- read.csv2("MASTERFILE_kleer_20210305.csv") ``` ```{r} data$Group <- factor(data$Group, levels = c("NHS", "SLE")) #SLE <- systemic lupus erythematosus group #NHS <- normal human serum (actualy has been plasma) ``` ```{r} wilcox.test(Age ~ Group, data=data) # SLE and Control Group are not age matched ``` ```{r} #create data.frame SLEsubset for demographic and clinical characteristics of SLE patients SLEsubset <- data[1:378, 1:256] ``` ```{r} #create data.frame NHSsubset for Demographic and clinical characteristics of healthy blood donors (control group) NHSsubset <- data[379:478, 1:256] ``` ```{r} #create continuous and categorical variables for summary statistics #Enthnical Background SLEsubset$ENBG <- factor(SLEsubset$ENBG, levels = c(1,2,3,4,5), labels = c("Caucasian", "Asian", "African", "native American", "other")) #create variable 1=active Disease, 0= inactive Disease SLEsubset$PGA <- factor(SLEsubset$PGA,levels = c("inactive","moderat", "active", "very active"),labels = c(1,2,3,4)) SLEsubset$PGA <- as.numeric(SLEsubset$PGA) SLEsubset$activity <- ifelse(SLEsubset$SELENA>=6 & SLEsubset$PGA >=2, yes=1,no=0) SLEsubset$activity <- factor(SLEsubset$activity, levels = c(0,1), labels=c("inactive", "active")) #Fever SLEsubset$FEV <- factor(SLEsubset$FEV, levels = c(0,1), labels = c("no", "yes")) #Arthritis SLEsubset$ARI <- factor(SLEsubset$ARI, levels = c(0,1), labels = c("no", "yes")) #skin involvement SLEsubset$skin_involvement <- ifelse(SLEsubset$MAL == 1 | #Malar rash SLEsubset$APH == 1| #Mucosal ulcers SLEsubset$ALO == 1, yes = 1, no= 0) #Alopecia SLEsubset$skin_involvement <- factor(SLEsubset$skin_involvement, levels = c(0,1), labels = c("no", "yes")) #Vasculitis SLEsubset$EVA <- factor(SLEsubset$EVA, levels = c(0,1), labels = c("no", "yes")) #Pericarditis or Pleuritis SLEsubset$PLEPER <- ifelse(SLEsubset$PER ==1 | SLEsubset$PLE == 1, yes = 1, no= 0) SLEsubset$PLEPER <- factor(SLEsubset$PLEPER, levels = c(0,1), labels = c("no", "yes")) #CNS-Involvement SLEsubset$CNSinvolvement <- ifelse(SLEsubset$PSY ==1 | #Psychosis SLEsubset$SEI ==1 | #Seizures SLEsubset$OBD ==1, yes = 1, no=0) #organic Brain Syndrome, SLEsubset$CNSinvolvement <- factor(SLEsubset$CNSinvolvement, levels = c(0,1), labels = c("no", "yes")) #Leukopenia SLEsubset$LEU <- factor(SLEsubset$LEU, levels = c(0,1), labels = c("no", "yes")) #Thrombocytopenia SLEsubset$PLA <- factor(SLEsubset$PLA, levels = c(0,1), labels = c("no", "yes")) #Proteinuria SLEsubset$PRO <- factor(SLEsubset$PRO, levels = c(0,1), labels = c("no", "yes")) #Hematuria SLEsubset$HUM<- factor(SLEsubset$HUM, levels = c(0,1), labels = c("no", "yes")) #low Complement SLEsubset$TCO <- factor(SLEsubset$TCO, levels = c(0,1), labels = c("no", "yes")) #anti-ds-DNA SLEsubset$DNA<- factor(SLEsubset$DNA, levels = c(0,1), labels = c("no", "yes")) #Amemia SLEsubset$Anemia <- ifelse(SLEsubset$sex == "Female" & SLEsubset$HGB < 120, yes= 1, no = ifelse(SLEsubset$sex == "Male" & SLEsubset$HGB < 130, yes=1, no=0)) SLEsubset$Anemia <- factor(SLEsubset$Anemia, levels = c(0,1), labels = c("no", "yes")) # elevated erythrocyte sedimentation rate SLEsubset$ESRelevated <- ifelse(SLEsubset$sex == "Female" & SLEsubset$Age <= 50 & SLEsubset$ESR > 20, yes=1, no = ifelse(SLEsubset== "Female" & SLEsubset$Age > 50 & SLEsubset$ESR > 30, yes=1, no = ifelse(SLEsubset$sex == "Male" & SLEsubset$Age <=50 & SLEsubset$ESR > 15, yes=1, no = ifelse(SLEsubset$sex == "Male" & SLEsubset$Age > 50 & SLEsubset$ESR > 20, yes= 1, no= 0 )))) SLEsubset$ESRelevated <- factor(SLEsubset$ESRelevated, levels = c(0,1), labels = c("no", "yes")) #Antiphospholipid-Antibodies SLEsubset$APA[SLEsubset$APA == "Present"] <- 1 SLEsubset$APA[SLEsubset$APA == "Absent"] <- 0 SLEsubset$APA[SLEsubset$APA == 99] <- NA SLEsubset$APA <- as.numeric(SLEsubset$APA) SLEsubset$APA <- factor(SLEsubset$APA, levels = c(0,1), labels = c("no", "yes")) ``` ```{r} # create variable list for Table one (SLE patients) variablesSLE <- c("sex", "NACRC", "ENBG", "Age", "DDDXBE", "activity", "FEV", "ARI", "skin_involvement", "EVA","PLEPER", "CNSinvolvement", "LEU","PLA","PRO","HUM","TCO","DNA", "Anemia", "ESRelevated", "APA") #Create Table one tableoneSLE <- CreateTableOne(data=SLEsubset, vars= variablesSLE) #Summary of Table one summary(tableoneSLE) ``` ```{r} # create variables for Table one from (Control Group) variablesNHS <- c("sex", "Age") #Create Table one tableoneNHS <- CreateTableOne(data=NHSsubset, vars= variablesNHS) #Summary of Table one summary(tableoneNHS) ```